Search Results (2,189)

Enterprise bankruptcy prediction is a critical research issue in financial risk early warning, credit evaluation, and investment decision-making. To address the limitations of traditional methods in handling high-dimensional, nonlinear, and complex financial data, including parameter sensitivity, susceptibility to local optima, and insufficient prediction stability, this study proposes a multi-strategy enhanced Beaver Behavior Optimizer and applies it to optimize kernel extreme learning machines, constructing the MEBBO KELM prediction model. Three improvement mechanisms are introduced, including an elite pool enhanced exploration strategy, a stochastic centroid reverse learning strategy, and a leader guided boundary control strategy, which improve population diversity, global search capability, boundary handling capacity, and convergence accuracy. The proposed algorithm is evaluated on CEC2017 and CEC2022 benchmark datasets and compared with EWOA, HPHHO, MELGWO, TACPSO, CFOA, ALA, AOO, RIME, and BBO. Statistical analyses are conducted using the Wilcoxon rank sum test and the Friedman test. The results demonstrate that MEBBO achieves superior solution accuracy and stability, indicating strong global optimization capability and robustness. Further experiments on the Wieslaw Corporate Bankruptcy Dataset show that MEBBO-KELM achieves strong and robust performance across multiple evaluation metrics, including ACC, MCC, Sensitivity, Specificity, Precision, Recall, and F1 score. Specifically, ACC reaches 79.7578, MCC reaches 0.6050, and F1 score reaches 78.8504, confirming its effectiveness. Full article

The integration of environmental, social and governance (ESG) criteria into corporate and financial decision-making has become one of the most significant transformations in today’s financial markets. Growing regulatory pressure, stakeholder expectations and increased awareness of sustainability challenges have led companies and investors to incorporate ESG considerations into strategic and investment decisions. Despite the rapid spread of ESG practices, the academic literature presents conflicting and sometimes contradictory evidence regarding their economic implications and practical effectiveness. This article provides a review of the literature on the main academic contributions to ESG integration, focusing on three key dimensions: the economic benefits associated with ESG practices, the methodological and credibility challenges relating to ESG measurement, and the organisational and technological factors that enable effective ESG implementation. The findings indicate that ESG integration is generally associated with positive organisational outcomes, including improved financial performance, lower cost of capital, greater stakeholder trust and a reduction in firm-specific risk. However, the realisation of these benefits is not automatic and depends to a large extent on the credibility of ESG practices and information. Rather than endorsing the widely held view that ESG criteria are inherently capable of creating value, the analysis shows that the value-creating effect of ESG criteria depends crucially on the credibility of ESG practices and the quality of their implementation. The literature highlights significant methodological challenges, including rating divergence, the lack of standardised metrics, methodological opacity and the growing risk of greenwashing, which can undermine the reliability of ESG information. This paper proposes an deductive conceptual framework in which ESG effectiveness emerges from the interaction between value creation mechanisms, credibility constraints, and enabling organisational and technological factors. Full article

Environmental, social, and governance (ESG) performance has become an important component of corporate sustainability and responsible governance, yet its economic implications remain contested, especially in state-owned enterprises (SOEs) that are expected to balance commercial goals with broader social responsibilities. This study examines the relationship between ESG performance and firm performance in Chinese listed SOEs, with particular attention to the mediating role of corporate reputation. The results show that ESG performance is positively associated with firm performance. Corporate reputation, risk-taking, and financial constraints are identified as important transmission channels through which ESG performance affects firm outcomes. Further analysis reveals a threshold effect in the ESG–performance relationship: when corporate reputation is relatively low, ESG investment may weaken firm performance; however, once reputation exceeds a critical threshold, ESG performance significantly improves firm performance. These findings enrich the literature on corporate sustainability and ESG value creation by showing that the performance effect of ESG is conditional on reputational capital. The study also provides practical implications for managers and policymakers seeking to promote sustainable corporate transformation in state-owned enterprises. Full article

Mandatory Environmental, Social, and Governance (ESG) disclosure requirements—anchored in Corporate Sustainability Reporting Directive (CSRD), International Sustainability Standards Board (ISSB), and Task Force on Climate-related Financial Disclosures (TCFD)—have placed unprecedented demands on supply chain data quality and auditability. Blockchain technology, combining immutability, decentralised governance, and smart contract automation, has emerged as a candidate infrastructure for addressing verification deficits across multi-tier supply chains. To our knowledge, no prior systematic review has simultaneously examined the blockchain specifically for formal ESG transparency and sustainability reporting across all three ESG dimensions within the post-CSRD mandatory reporting landscape. This study presents a systematic literature review (PRISMA 2020). Scopus and Web of Science searches identified 1,166 records (2016–2026); after deduplication, 761 unique records were screened, and after blinded screening (κ = 0.84), 96 studies were included. Five blockchain application typologies are identified (T1–T5), spanning provenance tracing, smart contract compliance, carbon accounting, supplier data aggregation, and ESG disclosure systems. A structural asymmetry is identified: governance is addressed in 96% of studies (77.1% under the strictest G-CONFIRMED recoding; 95.8% under the moderate interpretation, including borderline cases), the environmental pillar in 49%, and the social dimension in 21%, explained through institutional theory, with significant implications for CSRD and Corporate Sustainability Due Diligence Directive (CSDDD). Key barriers include scalability, interoperability, and the blockchain–GDPR (General Data Protection Regulation) tension. Three principal contributions are made: (i) a systematic typology of blockchain for ESG transparency; (ii) institutional-theory explanation of ESG dimension asymmetry; and (iii) a research agenda centred on AI–blockchain convergence and post-CSRD empirical studies. The review is limited to English-language peer-reviewed literature. Full article

Financial reporting integrity (FRI) plays a critical role in capital market efficiency, yet its determinants remain difficult to model due to nonlinear relationships, heterogeneous firm characteristics, and institutional differences across emerging markets. Prior research largely relies on linear econometric approaches, which may overlook threshold effects and complex governance dynamics. This study develops an explainable Optuna-optimized Extremely randomized trees (ET) ensemble framework to examine the association between controlling shareholders and FRI in Egypt and Saudi Arabia. Using a panel dataset of 1746 firm-year observations over the period 2014–2022, the model incorporates advanced preprocessing and mutual information-based feature selection to enhance predictive accuracy and robustness. The proposed model significantly outperforms regularized linear models, standalone machine learning models, and alternative ensemble techniques, achieving R² values of 0.7935 in Egypt and 0.9231 in Saudi Arabia, alongside substantial reductions in RMSE and MAE. Diebold–Mariano tests confirm that these performance gains are statistically significant (p < 0.01). Explainability analysis using SHAP reveals that firm size and market share are the dominant drivers of FRI, while blockholder ownership exhibits a nonlinear and context-dependent association. Partial dependence results show a complex, non-monotonic relationship in Egypt—consistent with a monitoring–entrenchment trade-off—contrasted with a predominantly positive and monotonic association in Saudi Arabia. Importantly, these nonlinear patterns are not detected in conventional panel fixed effects models, highlighting the limitations of standard econometric specifications in capturing complex ownership dynamics. The findings highlight the importance of institutional context in shaping governance outcomes and demonstrate how explainable ensemble learning can uncover hidden nonlinearities in financial reporting behavior. This study contributes by identifying nonlinear thresholds and cross-country variation in ownership effects while integrating predictive performance with interpretability, offering a robust framework for analyzing corporate governance mechanisms in emerging markets and supporting more informed decision-making by investors, regulators, and policymakers. Full article

Ecologically fragile regions face the dual challenge of environmental conservation and improving rural livelihoods. Forest-dependent households are especially exposed to ecological restoration constraints, market fluctuations, and limited institutional access. This study develops a micro-level diagnostic framework that combines the Sustainable Livelihood Framework with resilience theory by adding a risk-resilience dimension to the conventional five-capital structure. Using survey data from 444 forest-farmer households in Songshan District, Inner Mongolia, we calculate livelihood resilience with the entropy-weight method, classify household profiles with K-means clustering, and diagnose constraints with an obstacle-degree model. The mean resilience score is 0.6267, indicating a relatively strong but uneven resilience level. Livelihood risk resilience (0.7476) and financial capital resilience (0.6797) are the strongest dimensions, whereas human capital resilience (0.3521) and physical capital resilience (0.4099) remain weak. The main obstacles are relationships with village cadres (29.66%), household savings (16.25%), livestock and poultry assets (14.70%), village road conditions (13.23%), relationships with relatives and friends (10.99%), and corporate/cooperative assistance effects (6.88%). The findings support targeted interventions in linking social capital, savings capacity, infrastructure, and enterprise-farmer cooperation. Full article

The objective of this study was to explore the impact of exchange rate volatility on corporate financial stability in European corporations, with particular emphasis on the Eurozone and non-Eurozone. The data set of this study consisted of 80 publicly listed non-financial corporations in eight European countries over the period of 2010–2024. The model was able to capture the impact of various macroeconomic changes that affected European corporations in the past few years. The macroeconomic changes that were captured in this study were the European sovereign debt crisis, the COVID-19 pandemic in the world, and the conflict in Ukraine. The financial stability was measured by the Altman Z-score, the leverage ratio, and the current ratio. In this study, the financial impact of the exchange rate was measured by the rolling standard deviations and the conditional volatility with the Generalized Autoregressive Conditional Heteroskedasticity (GARCH) models. The fixed effects model estimation with the System Generalized Method of Moments (GMM) was used in this study. The results of this study showed that the exchange rate volatility was negatively correlated with financial stability in terms of the leverage ratio. However, the Eurozone provides protection against the financial impact of the exchange rate volatility in terms of the leverage ratio. The diagnostic tests in this study were carried out with the Hansen Test and the Arellano-Bond Test. The diagnostic tests confirmed that the results were valid. The significance of this study was that it provided longitudinal data on the impact of the exchange rate on the financial stability of European corporations with particular emphasis on the Eurozone and non-Eurozone. The study also provided new insights on the exchange rate in corporate finance. The Eurozone provides protection against the financial impact of the exchange rate. Full article

The evolution from Industry 4.0 to Industry 6.0 represents a paradigm shift—moving from automation toward an integrated model that incorporates intelligentization, sustainability, and human-centric resilience. While numerous conceptual frameworks have been put forward, empirical research remains scarce, primarily because of the absence of standardized indicators derived from verifiable corporate disclosures. To fill this research gap, the present study develops three quantifiable indices—Intelligence (INT), Sustainability (SUS), and Resilience & Human-centric (RES)—by extracting data from the annual reports and ESG disclosures of 100 Chinese A-share manufacturing enterprises (covering 2022–2024). Fixed-effects panel regression models are employed to assess the impact of these indices on financial performance (ROA, ROE, EPS), market valuation (Tobin’s Q), and sustainability outcomes (ESG ratings). Our findings reveal that INT is the most significant predictor of profitability, with statistically significant positive effects on ROA and ROE—effects that are particularly pronounced among high-tech enterprises. This supports the view that digital capabilities serve as strategic assets. SUS also demonstrates a positive influence on performance, especially in non-high-tech enterprises, where eco-efficiency, regulatory compliance, and ESG-linked financing help offset technological disadvantages. RES contributes to operational and financial stability by enhancing human capital, safety protocols, and organizational practices that reduce performance volatility. Collectively, these results indicate that different types of enterprises follow distinct yet converging pathways toward Industry 6.0: high-tech enterprises capitalize on intelligence to generate innovation rents, while non-high-tech enterprises increasingly rely on sustainability and resilience as strategies to build legitimacy. This study makes significant contributions in three aspects: Methodologically, it differs from previous research that relies on questionnaires and interviews. Instead, it quantifies Industry 6.0 through auditable large-sample key indicators, enhancing the objectivity and operability of the indicators. Empirically, it provides the first empirical evidence on the development path of Industry 6.0 based on data from Chinese manufacturing enterprises. In practical terms, it offers clear references for enterprises and policymakers on the core indicators and their construction framework that should be prioritized during the transformation to Industry 6.0. By linking the index derived from enterprise disclosures with quantifiable performance results, this study effectively bridges the gap between theoretical conceptions and practical applications. It further emphasizes that Industry 6.0 is not merely a technological upgrade but a systematic transformation driven by digitalization, sustainability, and resilience aimed at enhancing enterprise performance and achieving sustainable industrial development. Full article

This study investigates the role of market volatility, proxied by the CBOE Volatility Index (VIX), as a potential regime-dependent interaction of corporate leverage risk within the S&P 100. Addressing the limitations of traditional financial distress models in capturing non-linear and regime-dependent dynamics, we employ XGBoost combined with SHAP-based explainable AI (XAI) on a longitudinal dataset spanning 2000–2025. The results show that Total Debt remains the dominant predictor of financial distress, while the predictive contribution of risk-related variables such as the VIX and equity returns increases during crisis periods. Monetary policy indicators become more important during pandemic conditions, whereas inflation dominates in a stable environment. This finding highlights the regime-dependent nature of financial risk drivers and demonstrates the value of explainable machine learning in developing interpretable risk diagnostic frameworks. By integrating predictive accuracy with interpretability, this study provides new insights into the non-linear interaction between firm-level leverage and external market volatility. Full article

This study provides the first empirical analysis of how energy-sector corporate filing events transmit to financial markets, bridging a critical gap between corporate financial distress literature and commodity market dynamics. The analysis employs an event study methodology with Wilcoxon signed-rank tests and panel regression models to examine 51 U.S. energy firms that experienced financial distress (2015–2021) across the NYSE and NASDAQ. Post-announcement cumulative abnormal returns (CARs) show positive median values (WSR: 40.5 for NYSE in 10-day window, p < 0.10; 97.8 for NASDAQ in 10-day window, p < 0.05; 36.24 for NASDAQ in 5-day window, p < 0.10). Panel regression results show significant differences in post-announcement CARs relative to the event day for both indices (NYSE: 10-day window coefficient = 117.1, p < 0.05; NASDAQ: 10-day = 199.6, p < 0.01; 5-day = 150.8, p < 0.05), as well as in pre-announcement windows for NYSE (5-day coefficient = 93.5, p < 0.10; 10-day = 86.6, p < 0.10). The findings suggest that markets respond to energy-sector corporate distress events without broad-based disruption, likely due to early signals of financial distress, clarified expectations regarding recovery paths under Chapter 11 restructuring, and reduced information asymmetry through disclosures. Policymakers can leverage these insights to refine corporate filing frameworks for commodity-dependent sectors. Full article

Corporate crime is a widespread societal issue that causes significant physical, emotional, and financial harm. Despite its prevalence, research examining its effects from a public health perspective remains limited. This viewpoint paper, informed by a systematic review, examines the relationship between corporate crime and mental health, highlighting potential associations and methodological gaps. Evidence from OECD countries identified only two empirical studies, both conducted in Spain, both focusing on financial fraud, leaving other forms of corporate wrongdoing largely underexplored. The discussion is guided by a conceptual framework linking corporate financial violations to mental health outcomes, integrating stress theory, social determinants of health, and bidirectional pathways in which mental health may also influence corporate crime. The paper outlines a research agenda for public health researchers, addressing priority populations, study designs, measurement approaches, and policy implications. By bridging criminology and public health perspectives, this approach offers both theoretical insight and practical guidance for understanding and mitigating the mental health impacts of corporate crime. This framework constitutes the paper’s primary conceptual contribution by explicitly integrating criminological and public health perspectives into a multi-level and bidirectional model that has not been systematically articulated in prior literature. Rather than providing generalisable OECD-wide evidence, the paper highlights a substantial empirical gap within OECD settings and identifies key directions for future research. Full article

Earnings management undermines financial transparency and threatens long-term corporate sustainability, particularly in emerging markets where principal–agent conflicts remain pronounced. In China’s capital market, performance-based incentives may motivate managers to manipulate reported earnings, thereby impairing investor protection and governance quality. Despite growing interest in enterprise risk management (ERM) as a holistic governance mechanism, empirical evidence on its effectiveness in constraining earnings manipulation remains limited. This paper investigates the governance role of ERM in mitigating both accrual-based earnings management (AEM) and real earnings management (REM) among Chinese listed firms over the period 2019–2024. Using panel regression models, this study examines whether higher ERM engagement is associated with lower levels of earnings manipulation. The results indicate that ERM is significantly and negatively related to both AEM and REM. These findings remain robust to alternative variable definitions, different sample period specifications, interaction analyses between accrual-based and real earnings management, alternative constructions of ERM (including PCA-based measures and exclusion of reporting-related components), and endogeneity tests using industry–year average ERM as a proxy. Further heterogeneity analyses reveal that the constraining effect of ERM on REM is more pronounced in firms audited by non-Big Four auditors, while the effect is weaker in Big Four audited firms. Overall, the evidence suggests that ERM functions as an effective internal governance mechanism that enhances financial reporting quality and supports sustainable corporate performance. This paper contributes to the sustainability and corporate governance literature by providing empirical evidence from an emerging market context and offers practical implications for regulators and corporate decision-makers seeking to strengthen risk governance frameworks. Full article

Despite the rapid institutionalization of ESG reporting mandates worldwide, the empirical question of whether ESG disclosure constitutes a structural, long-run determinant of corporate financial performance—rather than a cyclical or spurious co-trending artifact—remains unresolved. The prior literature predominantly employs short-panel estimators that assume stationarity and conflate long-run equilibrium effects with transitory associations. This study addresses that gap by applying a five-step non-stationary panel econometric framework to a sample of 479 S&P 500 firms across eleven GICS sectors over 2010–2022 (5084 firm-year observations), a period chosen to capture the full institutionalization of Bloomberg ESG reporting standards and to encompass two major macroeconomic stress episodes (the 2015–2016 commodity downturn and the COVID-19 shock). Im–Pesaran–Shin panel unit root tests confirm that ESG disclosure scores and financial performance measures are both integrated of order one. Pedroni residual-based panel cointegration tests decisively reject the null of no long-run relationship (Z = −62.38 for the ROA equation), establishing a stable cointegrating equilibrium. Fully Modified OLS and Dynamic OLS group-mean estimators yield bias-corrected long-run coefficients, and a panel error correction model quantifies short-run adjustment dynamics. The key finding is that a ten-point improvement in ESG disclosure is associated with a permanent nine-to-ten percentage-point gain in return on equity (FMOLS β = +1.023, p < 0.01; DOLS β = +0.914, p < 0.01), while the effect on return on assets is positive but more modest and sensitive to estimator choice. Complementary fixed-effects regressions reveal an asymmetric moderating role of macroeconomic uncertainty: equity market volatility (VIX) amplifies the ESG performance premium, whereas acute credit market stress (TED spread) attenuates it. Board governance variables are statistically insignificant across all five specifications, indicating that H3 (board governance) is not supported; this outcome is attributed to limited within-firm governance variation in the large-cap S&P 500 universe rather than a genuine absence of governance effects. The results are robust to lagged ESG measurement, winsorization, and alternative interaction specifications. The findings provide strong econometric evidence for the structural, permanent nature of the ESG–financial performance link in large-cap U.S. equities, with direct implications for mandatory disclosure policy and ESG-integrated investment strategies. Full article

This study explores the impact of internationalization on the financing decisions and finance costs of Chinese enterprises listed in Hong Kong, extending the pecking order theory to an international context. Utilizing data from 785 companies from 2010 to 2020, the research investigates how the degree of internationalization influences corporate finance strategies, with a focus on the mediating role of the pecking order and the moderating effects of international business factors. The findings reveal that while broader internationalization increases finance costs, deeper internationalization reduces them. Legal distance is found to negatively moderate this relationship, whereas the structure of the financial system positively influences it. The results suggest that multinational enterprises with extensive overseas resource allocation demonstrate greater flexibility in financing decisions, particularly in foreign markets characterized by strong investor protection and efficient direct finance mechanisms. Managers should be cautious about pursuing wide geographic expansion without adequate operating depth because a broad but shallow international presence may increase financing frictions. By contrast, deeper resource commitment abroad can strengthen financing flexibility and improve access to lower-cost funds, especially when institutional conditions in the financing market are favorable. Full article

This conceptual framework paper critically evaluates the economic, regulatory, and accounting significance of transparent reporting on investments in employee happiness, emphasizing its potential to reduce information asymmetry in capital markets. We define employee-happiness investments as deliberate organisational expenditures and management practices designed to enhance employees’ overall life satisfaction. Information asymmetry, a condition that occurs when managers possess better information than investors, poses substantial risks including market inefficiencies, misallocation of capital, and increased costs of capital. Empirical evidence consistently illustrates that employee happiness is positively correlated with enhanced firm productivity, lower risk, and improved financial performance. Despite these clear linkages, current international accounting and regulatory frameworks do not adequately capture investments in employee happiness, with International Accounting Standard 38 mandating immediate expensing rather than balance sheet recognition due to identifiability and control constraints. This treatment could exacerbate informational disparities and may potentially hinder effective investor decision-making by obscuring strategic resource allocation patterns within aggregated expense line items. Drawing on recent studies and real-world financial outcomes, the paper argues for complementary disclosure reforms mandating standardized reporting of employee-happiness investments and outcomes as a crucial step toward more informed market assessments and sustainable corporate practices. Full article